Introduction
IBM Research takes responsibility for technology and its role in society. Working in IBM Research means you'll join a team who invent what's next in computing, always choosing the big, urgent and mind-bending work that endures and shapes generations. Our passion for discovery, and excitement for defining the future of tech, is what builds our strong culture around solving problems for clients and seeing the real world impact that you can make.
IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive.
Your Role and Responsibilities
You will play a crucial role in enhancing our machine learning infrastructure. The ideal candidate will have a solid foundation in DevOps practices and tools, enabling seamless integration and deployment of machine learning models. You will be responsible for automating workflows, managing CI/CD pipelines, and ensuring the reliability and scalability of our ML applications. In addition to your DevOps skills, you should possess a strong understanding of machine learning concepts, including AI inferencing and benchmarking techniques. You will collaborate closely with AI researchers and engineers to optimize model test performance and streamline deployment processes. If you are passionate about bridging the gap between development and operations in the rapidly evolving field of AI, we'd love to hear from you.
Want more jobs like this?
Get Software Engineering jobs delivered to your inbox every week.
Todas as vagas são elegíveis para pessoas com deficiência ou reabilitadas.
Required Technical and Professional Expertise
1-DevOps Expertise Proficient in CI/CD tools (e.g., Jenkins, GitLab CI) Experience with containerization (Docker, Podman, Kubernetes)
2-Machine Learning Knowledge Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) Experience with AI inferencing and deployment of LLM models
3-Scripting and Programming Proficient in scripting languages (e.g., Python, Bash) Experience with at least one programming language (e.g., Java, Go, C++)
4-Version Control Proficient in Git and GitHub for version control and collaboration
5- Fluent English
Preferred Technical and Professional Expertise
1-LLM (Large Language Model) Expertise Understanding of LLM architectures (e.g., GPT, BERT) and their applications Experience fine-tuning and deploying LLMs in production
2-OpenShift Architecture Understanding of OpenShift components (e.g., nodes, pods, services, routes)
3-Kubernetes Knowledge Familiarity with Kubernetes concepts and APIs, as OpenShift is built on Kubernetes
4-Monitoring and Logging Familiarity with monitoring tools (e.g., Prometheus, Grafana) and logging systems (e.g., ELK Stack)
5-Collaboration Tools Experience with Agile methodologies and tools (e.g., Jira, Trello)
6-Soft Skills Strong communication and teamwork abilities Problem-solving mindset with attention to detail